Results 111 to 120 of about 147,704 (285)

Learnable Diffusion Framework for Mouse V1 Neural Decoding

Advanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng, Peter S. Schwendeman, Yuanfang Guan   +2 more
wiley   +1 more source

Side information-driven image coding for hybrid machine–human vision

EURASIP Journal on Image and Video Processing
With the development of machine learning, advanced photography and image transmission systems, images are being processed more and more by machines, so image coding for machines (ICM) came into being.
Zhongpeng Zhang, Ying Liu, Wen-Hsiao Peng   +2 more
doaj   +1 more source

Semantic and Structural Image Segmentation for Prosthetic Vision

Jornada de Jóvenes Investigadores del I3A, 2019
We present a new approach to build a schematic representation of indoor environments for phosphene images. The proposed method combines a variety of convolutional neural networks for extracting and conveying relevant information about the scene such as structural informative edges of the environment and silhouettes of segmented objects.
Melani Sanchez-Garcia, Ruben Martinez-Cantin, Jose J. Guerrero   +2 more
openaire   +7 more sources

GloPath: An Entity‐Centric Foundation Model for Glomerular Lesion Assessment and Clinicopathological Insights

Advanced Science, EarlyView.
An entity‐centric foundation model, GloPath, is introduced for comprehensive glomerular lesion assessment from routine renal biopsy images. Trained on over one million glomeruli, the framework enables robust lesion recognition, grading, and cross modality diag nosis, while uncovering large‐scale clinicopathological associations.
Qiming He, Jing Li, Tian Guan, Yifei Ma, Zimo Zhao, Yanxia Wang, Hongjing Chen, Yingming Xu, Shuang Ge, Yexing Zhang, Yizhi Wang, Xinrui Chen, Lianghui Zhu, Yiqing Liu, Qingxia Hou, Shuyan Zhao, Xiaoqin Wang, Lili Ma, Peizhen Hu, Qiang Huang, Zihan Wang, Zhiyuan Shen, Junru Cheng, Siqi Zeng, Jiurun Chen, Zhen Song, Chao He, Zhe Wang, Yonghong He   +28 more
wiley   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

Advanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang, Yang Wu, Feng Zhang, Parthiban Periasamy, Haiyue You, Denise Goh, Rachel Elizabeth Ann Fincham, Xin Ning, Danping Wu, Lu Liu, Ying Jiang, Zhiwen Qian, Joe Yeong, Yan Zhang   +13 more
wiley   +1 more source

A multilevel segmentation method of asymmetric semantics based on deep learning

IET Cyber-Physical Systems
An asymmetric semantic multi‐level segmentation method based on depth learning is proposed in order to improve the precision and effect of semantic segmentation.
Angxin Liu, Yongbiao Yang
doaj   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Explainable AI (XAI) in image segmentation in medicine, industry, and beyond: A survey

ICT Express
Explainable AI (XAI) has found numerous applications in computer vision. While image classification-based explainability techniques have garnered significant attention, their counterparts in semantic segmentation have been relatively neglected. Given the
Rokas Gipiškis, Chun-Wei Tsai, Olga Kurasova   +2 more
doaj   +1 more source

Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare

Advanced Science, EarlyView.
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu, Haolin Fan, Minwoo Kim, Tong Zhou, Pinyi Yang, Lingdi Zhao, Yiran Wang, Ziyuan Che, Chia‐Wei Liu, Bingbing Li, Yangzhi Zhu   +10 more
wiley   +1 more source

Semantic segmentation of agricultural images: A survey

Information Processing in Agriculture
As an important research topic in recent years, semantic segmentation has been widely applied to image understanding problems in various fields. With the successful application of deep learning methods in machine vision, the superior performance has been
Zifei Luo, Wenzhu Yang, Yunfeng Yuan, Ruru Gou, Xiaonan Li   +4 more
doaj   +1 more source